Electronic commerce websites are continually being refined to retain users on the website and entice the user to purchase items, services, or take other actions that will result in an increase in the website's revenue. A variety of statistical tools have been developed to test graphical aspects of a web page to determine the type and layout of graphical content on a web page that may be most effective at inducing a purchase or other desired action. For example, split testing may be used to test two versions of a web page or multi-variate testing may be used to test a multitude of content variations in a web page.
However, prior split testing systems suffer from the drawback that the type of content that they can test is limited to static content, which is content that remains unchanged when presented on to users in a variety of different computing sessions. In contrast, dynamic content, which is content that is programmatically determined by the website servers and thus may vary based on user browsing history, state, etc., cannot be tested. The inability to apply such split testing methodologies to dynamic website content prevents website owners from more fully understanding the behavior of their customers and the effectiveness of their website.